Measurement Optimization for Localization using Modeled Radio Maps and Compressive Sensing

Location information is an important enabler for context-aware services and communication system improvement. Localization can be performed by comparing the power readings of all surrounding wireless transmitters to a database of these readings at all possible locations, known as the radio map. For this localization process to work, the system requires accurate radio maps. Our industrial partner, Siradel, have designed a software to create modeled estimates of radio maps for any site, which need to be refined with measurements. These measurements are costly if a high level of accuracy is required.

Our role is to develop limited measurement schemes (schemes performing a small number of measurements) that can Increase the accuracy of the modeled radio maps, enhance the fidelity of the location estimation using the improved radio maps, and dynamically update and refine the radio map according to site changes.

The results of this project will help our industrial partner in both refining their modeled radio maps with minimum measurement cost, and building accurate and affordable localization systems that are easily commercialized.

Faculty Supervisor:

Dr. Shahrokh Valaee

Student:

Sameh Sorour

Partner:

SURADEL Canada

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Toronto